The present invention relates to a character recognition apparatus, and more particularly to a character recognition apparatus which previously prepares a plurality of standard character patterns as dictionary patterns to be compared with an input character pattern.
In a conventional character recognition apparatus of this kind, an input character pattern is compared exhaustively with dictionary patterns of a plurality of categories (0 to 9, for example, in a numerical character). In this case, a plurality of dictionary patterns are prepared with respect to one category in order to recognize various character shape modifications or various character fonts. Then, at least one dictionary pattern with the greatest degree of coincidence or the least degree of mismatch is detected and the character category corresponding to the detected dictionary pattern is determined finally as the basis for comparison with the input character pattern.
In the comparing process, though the input character pattern is compared with many dictionary patterns covering a plurality of categories, when the mismatch degree exceeds a predetermined threshold during the comparing operation, the comparison with this dictionary pattern is immediately interrupted so as to proceed with a comparison with the next dictionary pattern. When the mismatch degree does not exceed the threshold, a dictionary pattern along code corresponding to the dictionary pattern with the mismatch degree is sequentially stored in a memory. Based on this stored information, a dictionary pattern code with the least mismatch degree is finally selected, and a category corresponding to the code is obtained as a recognition result.
In an alternative recognition process, it is customary that not only a similarity to the dictionary pattern but also another factor, for example, the result of a recognition process for a previous character in an input character train, is used for synthetic recognition. In this case, in addition to the candidate with the greatest degree of coincidence (the lowest mismatch degree), other candidates having greater degrees of coincidence are also selected through the comparison process as candidates.
In conventional recognition apparatus, when an input character has been compared with all the dictionary patterns, dictionary pattern codes with corresponding mismatch degrees less than a predetermined threshold are stored in the memory. However, in this case, a plurality of dictionary pattern codes corresponding to the same category often are uselessly stored in the memory. Accordingly, an additional; process to detect the least mismatch degree in the same category is disadvantageously needed to deliver a plurality of categories having the least mismatch degrees as candidates.
In the above-described conventional character recognition apparatus, the comparison operation between an input pattern and a dictionary pattern is interrupted only when a mismatch degree exceeds a fixed predetermined threshold. When the mismatch degree does not exceed the threshold, a plurality of dictionary pattern codes with mismatch degrees corresponding to the same category are uselessly stored and a process to detect the least mismatch degree in the same category is necessary. As a result, the conventional character recognition apparatus requires a relatively long time for character recognition.